Physician performance and recommendation interface

ABSTRACT

The technology provides for utilizing and displaying physician analytics. For example, a result metric for a physician is based on a value metric, a quality metric, and/or a quantity metric. The value metric, quality metric, and/or quantity metric may all be received from different sources. The result metric may be displayed on a chart, or the result metric may be utilized for determining referral recommendations for a physician. The result metric may be displayed as a physician indicator on the chart. An insight for the physician may also be determined from the result metric. The insight may be based on the location of the physician indicator on the chart, and the insight may be represented by the color or other visual attribute of the physician indicator. For referral recommendations, the result metric may be used to adjust the rank of a physician in a referral search result.

INTRODUCTION

Hospitals and physician networks often strive to acquire and retain thephysicians that are of the highest-quality, while at the same timeensuring that the costs are controlled. Determining how to makeeffective choices to achieve that goal is often a highly-complexprocess. Health systems forming Accountable Care Organizations and othernetworks need tools to set strategy, analyze market data, measureperformance on internal quality and regulatory programs, manageperformance, and engage their clinicians. It is with respect to thisgeneral environment that embodiments of the present disclosure have beencontemplated.

SUMMARY

In one aspect of the technology, a method for displaying physiciananalytics is provided. The method includes receiving a value metric anda quality metric for the physician. The value metric may represent aphysician's value to a health system, whereas a quality metricrepresents the quality of care provided by the physician. Some examplesof a value metric include a physician's contribution margin or thephysician's revenue share. Some examples of a quality metric include30-day readmission rate, mortality rate, complications of care, or anycombination thereof. The value metrics and quantity metrics may alsocome from different sources, and may be selected or customized by theuser.

A result metric for the physician may also be determined based on thevalue metric and the quality metric for the physician. That resultmetric may be displayed in multiple forms. For example, the resultmetric may be displayed on a chart, where one axis of the chartrepresents the value metric for the physician and the other axis of thechart represents the quality metric for the physician. In the examplewhere the result metric is displayed on a chart, the result metric maybe displayed as a physician indicator. The size of the physicianindicator may be dependent on a quantity metric for the physician, whichmay also be received. The result metric may also be dependent on thereceived quantity metric.

Based on the result metric, insights for the physicians may also bedetermined. For example, the location of the physician indicator on achart may indicate that a particular insight should be associated withthe doctor. As an example, a physician may be considered a topcontributor if the respective physician indicator is in thecorresponding segment of the chart. The insights may be displayed as acolor of the physician indicator. For instance, one color or visualattribute of the physician indicator may correspond to a particularinsight. An insight legend may be included in or adjacent to the chartto explain the insights and their relationship to the color or visualattribute of the physician indicator. Physician indicators for multiplephysicians may also be displayed concurrently on the same chart.

Additional metrics and insights may also be provided for the physicianupon selecting a physician indicator from the chart. Upon selecting thephysician indicator, a physician performance analysis may be presentedthat includes various metrics and information regarding the particularphysician that corresponds to the physician indicator that was selected.

In another aspect of the technology, a referral recommendation may alsobe made for a physician. The recommendation may be based on the resultmetric for the physician. For example, the rank of a physician in aresults list for referrals may be adjusted based on the physician'sresult metric.

In all cases, the technology disclosed herein is intended to be usedsubject to all applicable laws of the pertinent jurisdiction. These aswell as other aspects, advantages, and alternatives will become apparentto those of ordinary skill in the art by reading the following detaileddescription, with reference where appropriate to the accompanyingdrawings. Further, it should be understood that this summary and otherdescriptions and figures provided herein are intended to illustrateembodiments by way of example only and, as such, numerous variations arepossible. For instance, structural elements and process steps can berearranged, combined, distributed, eliminated, or otherwise changed,while remaining within the scope of the embodiments as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

There are shown in the drawings, embodiments of the disclosure, it beingunderstood, however, that the disclosure is not limited to the precisearrangements and instrumentalities shown.

FIG. 1 depicts a system for implementing a physician performanceinterface, in accordance with embodiments of the invention.

FIGS. 2A-B depict an exemplary process flow for providing a physicianperformance interface.

FIGS. 3A-3D depict embodiments of a physician performance interface.

FIGS. 4A-B depict an embodiment of a physician performance analysis.

FIG. 5 depicts an exemplary process flow for determining a referralrecommendation.

FIG. 6 depicts an embodiment of a referral interface.

FIG. 7 illustrates one example of a suitable operating environment inwhich one or more of the present embodiments may be implemented.

FIG. 8 depicts an embodiment of a network in which the various systemsand methods disclosed herein may operate.

DETAILED DESCRIPTION

Embodiments of the present disclosure relate to a methods and systemsfor provided analysis, insights, and recommendations for physicianswithin a health system. A health system includes any environment inwhich physicians have some relationship to one another by virtue of arelationship to another entity, such as a hospital, network ofhospitals, or physician network. The embodiments of the presentdisclosure also provide for user interfaces to display information aboutphysicians and allow users to interact with the user interface.

FIG. 1 depicts a system 100 for implementing a physician performanceinterface. As depicted, a physician performance computing system 102receives data from multiple different sources. The physician performancecomputing system 102 may be implemented as a standalone or may befunctionally integrated into a health system administrator system 118 ora physician's office system 120, or any combination thereof. Thephysician performance computing system 102 receives information from oneor more insurance claims sources, collectively referred to herein as an“insurance claims source” 104. The insurance claims source 104 mayprovide information about physician market data, such as shares andrelationships, among other things. For instance, the insurance claimssource may provide information including inpatient and outpatientrevenue shares along with total revenue. Inpatient and outpatientvolumes and volume shares may also come from this source, in someembodiments. Payer mix information, such as the percentage of commercialinsurance versus Medicare, for physicians may come from this source aswell. The insurance claims source 104 may also provide informationregarding a freestanding, ambulatory, hospital or non-hospital facilityshare and referral sources. In addition, the insurance claims source 104may also provide information regarding referring physicians who haveshared patients over a specific time period. The insurance claims source104 may be, at least in part, the Crimson Market Advantage® productavailable from The Advisory Board Company of Washington, D.C. or datatherefrom.

The physician performance computing system 102 also receives data fromone or more inpatient billing data sources, collectively referred toherein as “an inpatient billing data source” 106. The inpatient billingdata source 106 may also include information from provider charge data.The inpatient billing data source 106 may provide information from whichquality metrics for physicians can be derived. For instance, the qualitymetrics information derived from provider charge data may includereadmission rates, such as the percent of readmissions within 30 days.The mortality rate for physicians may also be provided as well as thepercentage of discharges that have a follow-up appointment within sevendays. Other quality metrics such as preoperative care (e.g., venousthromboembolism prophylaxis) and coronary artery disease (CAD) lipidcontrol may be provided by the inpatient billing data source 106 (orderived from provider charge data provided by the inpatient billing datasource 106). In addition, other quality metrics may include thepercentage of three-day readmissions, the percentage of seven-dayreadmissions, the percentage of 30-day readmissions, complications ofcare, complications of condition, inpatient quality indicators, patientsafety indicators, pediatric quality indicators, cases with hospitalacquired conditions, complications of care/expected ration, coremeasures, hospital acquired conditions observed/expected ratio,mortality observed/expected ratio, mortality rate, percent ofreadmissions, and top complications of care, among others. The inpatientbilling data source 106 may comprise, at least in part, the CrimsonContinuum of Care® product available from The Advisory Board Company ofWashington, D.C., or data therefrom.

The physician performance computing system 102 also receives data fromone or more adjudicated insurance claims for managed care populationsources, collectively referred to herein as an “adjudicated insuranceclaims for managed care population source” 108. The adjudicatedinsurance claims for managed care population source 108 providescomprehensive longitudinal data for a specific patient population fromwhich information about population costs and efficiencies may bederived. The adjudicated insurance claims for managed care populationsource 108 may also provide additional information aboutpopulation-based quality metrics in addition to the quality metrics datapotentially received from other sources. For example, the informationfrom the adjudicated insurance claims for managed care population source108 may include attributed episode counts, average costs per episode,risk adjusted average costs per episode, percentage of high outlierepisodes, and generic utilization rates. The adjudicated insuranceclaims for managed care population source 108 may comprise, at least inpart, the Crimson Population Risk Management® product available from TheAdvisory Board Company of Washington, D.C., or data therefrom.

The physician performance computing system 102 further receives datafrom the practice billing system source 110 for example by interceptingoutgoing claims. The practice billing system source 110 providesinformation regarding ambulatory quality metrics such as PhysicianQuality Reporting System (PQRS) metrics, Healthcare Effectiveness Dataand Information Set (HEDIS) metrics, and e-prescribing data. Thepractice billing system source 110 may comprise, at least in part, theCrimson Continuum of Care® Ambulatory Module product available from TheAdvisory Board Company of Washington, D.C., or data therefrom.

The physician performance computing system 102 also receives data fromanother ambulatory EMR source 112 that provides information about riskprediction. The risk prediction information may be derived from both thedata within the ambulatory EMRs along with the free text notes withinthe ambulatory EMRs. The ambulatory EMR source 112 may comprise, atleast in part, the 360Fresh™ product available from The Advisory BoardCompany of Washington, D.C., or data therefrom.

The physician performance computing system 102 also receives data fromone or more practice management sources, collectively referred to hereinas a “practice management source” 114. The practice management source114 provides information about physician office productivity andefficiency metrics. For instance, the information may include averagetime for an appointment for a new patient, and the percentage of newpatients accommodated within fourteen days. Other information mayinclude available capacity, patient access, and work relative valueunits (wRVUs) for physicians. An RVU is the relative level of time,skill, training, and intensity to provide a given service and work isthe portion of reimbursement associated with the physician's work. Thepractice management source 114 may comprise, at least in part, theCrimson Medical Group Advantage™ product available from The AdvisoryBoard Company of Washington D.C., or data therefrom.

Yet another source for the physician performance computing system 102 isan internal hospital systems source 116, which may be comprised ofmultiple underlying sources. The internal hospital systems source 116provides information about hospital related activities such as cost ofsupplies and utilization of the operating room. For example, theinformation may include average contribution margin per case, averagecosts per case, average Length of Stay (LOS) per inpatient, and theaverage consultants used per case. The internal hospital systems source116 may comprise, at least in part, the Crimson Surgical ProfitabilityCompass® product available from The Advisory Board Company of WashingtonD.C., or data therefrom.

The data and information provided by each of the sources may also becategorized by a particular health system. For example, all datarelating to physicians in a particular health system, such as aphysician network or a hospital, may all be grouped together ordesignated as such. In some embodiments, indicating a physician's healthsystem may be accomplished by including metadata tags for allinformation that is received by the physician performance computingsystem 102. The physician performance computing system 102 may performadditional analysis to classify or categorize the data and informationbased on the health system of the physician.

In some embodiments, upon receipt of at least some of the informationand data provided by the data sources, the physician performancecomputing system 102 may store the data in a database 102A within thephysician performance computer system. In other embodiments, each of thedata sources continues to house the data separately and applicationprogramming interfaces (APIs) or other transfer mechanisms are utilizedto share data between data sources and the physician performancecomputing system 102. The physician performance computing system 102 mayalso determine whether the data requires further processing and analysisprior to being utilized in a physician performance interface for aphysician referral interface. Where additional processing and analysisis required, the physician performance computing system 102 performs theprocessing and data analysis. The analysis and processing may beperformed by the interface module 102B within the physician performancecomputing system 102. In some embodiments, the sources and the physicianperformance computing system 102 are integrated into a single computingsystem. In other embodiments, at least some of the sources are connectedvia a network, such as the Internet.

The physician performance computing system 102 utilizes the data toprovide an interactive interface to a user computer, such as a computerutilized by health system administrator 118 or a computer at oraccessible to a physician's office. The interfaces provided by thephysician performance computing system 102 are discussed in additionaldetail below. Each of the systems and sources may be implementedseparately by a computer system or server. The systems and sources mayalso be combined in one or more different combinations. Each of thesystems and sources may all be communicatively coupled to the physicianperformance computer system 102, and one or more of the sources maycommunicate with each other as well.

FIG. 2A depicts process flow for providing a physician performanceinterface. At operation 202, a physician performance interface componentwithin the physician performance computing system receives a valuemetric for a physician. The value metric may include data relating tophysician market data. The value metric may also indicate or relate themonetary value that a physician provides to a particular health system.For instance, the value metric may be the revenue share for a particularphysician. The revenue share for a particular physician is the amount ofthe physician's revenue that is within the health system. The revenueshare may be determined from the volume of claims for the physician andthen converted to an expected revenue payment, from which the revenueshare within the system may be determined. The revenue share may befurther refined to be the inpatient revenue share or the outpatientshare among other refinements. In embodiments, the value metric may bethe contribution margin or volume for the physician. The contributionmargin may be expressed as an amount equal to the revenue minus costsfor the physician for the physician's procedures that is contributed. Inother embodiments, the value metric is calculated from multiple types ofvalue-related data and metrics. Other value metrics may include wRVUs,patient access, efficiency metrics, attributed episode counts, averagecosts per episode, risk adjusted average costs per episode, per memberper month costs, and generic utilization rates. Receiving the valuemetric may include receiving the value metric from the sources depictedin FIG. 1. In other embodiments, receiving the value metric may be aninterface module receiving the value metric from a database within thephysician performance computing system.

The particular type of value metric, or the underlying data defining thevalue metric, may be selected or customized via user input. For example,user input may indicate a particular type of value metric that ispreferred. The user input may be in the form of a selection of a presetgroup of metrics to provide specific insights for a set of physicians.

A quality metric is received for a physician at operation 204. Thequality metric may include data relating to the quality of care providedby the physician. In some embodiments, the quality metric may be derivedfrom other underlying data as well. For example, the quality metric maybe a weighted quality score. The weighted quality score may be based onunderlying data, such as mortality rate, complications of care rate, andthe 30-day readmission rate. In embodiments, a specific weighted qualityscore, a “Z-score”, may be used. The Z-score is a score weighted asfollows: 50% weight to the 30-day readmission data, 30% weight for themortality rate, and 20% weight to the complications of care rate. Otherexamples of quality metrics include percentage of three-dayreadmissions, the percentage of seven-day readmissions, the percentageof 30-day readmissions, complications of care, complications ofcondition, inpatient quality indicators, patient safety indicators,pediatric quality indicators, cases with hospital acquired conditions,complications of care/expected ration, core measures, hospital acquiredconditions observed/expected ratio, mortality observed/expected ratio,mortality rate, percent of readmissions, and top complications of care,among others. Physician Quality Reporting System (PQRS) metrics,Healthcare Effectiveness Data and Information Set (HEDIS) metrics, ande-prescribing data may also be utilized. Additionally, quality metricssuch as percentage of high outlier episodes, evidence-based compliance,immunization records, avoidable admissions, avoidable emergencydepartment visits, and patient risk, may also be used. Similar to thevalue metric, the quality metric, or the underlying data defining themetric, may be selected or customized via user input. As such, thehealth system administrator, or another user, has the ability tocustomize what the user would like to see as a quality metric. Receivingthe quality metric may include receiving the quality metric from thesources depicted in FIG. 1. In embodiments, receiving the quality metricmay be an interface module receiving the quality metric from a databasewithin the physician performance computing system 102.

A quantity metric for a physician may also be received at operation 206.The quantity metric may be based on data such as the number thephysician's patients, the physician's case volume, the number ofoperations, or other similar quantity-based metrics for the physician.The quantity metric may also be the revenue share, revenue, volume, orother related data for the physician. The quantity metric may also beselected or customized via user input, similar to the value metric andthe quality metric. Receiving the quantity metric may include receivingthe quantity metric from the sources depicted in FIG. 1. In embodiments,receiving the quantity metric may be an interface module receiving thequantity metric from a database within the physician performancecomputing system 102.

At operation 208, a result metric is determined for the physician. Inembodiments, the result metric is determined based on at least the valuemetric and the quality metric received at operation 202 and operation204, respectively. The result metric may also be further based on thequantity metric. For instance, the result metric may be represented by acoordinate or a one-by-two matrix entry in a database, wherein the twovalues in the entry are the value metric and the quality metric. Inembodiments, the result metric is determined via an algorithm based onthe value metric and the quality metric. For instance, the value for thevalue metric and the value for the quality metric may be mathematicallycombined, e.g., added or multiplied, to receive a single value. Theresult metric may also be based on additional user input concerning howthe result metric should be determined from the value metric and thequality metric. In embodiments, the result metric may be based onadditional underlying data points in addition to the data utilized inthe value metric and the quality metric. For instance, the result metricmay be a combination of (1) the number of standard deviations thephysician's quality metric is from the mean quality metric of all theother physicians within a particular health network and (2) thepercentage of revenue share of the health system for the physician. Inembodiments, the result metric may be a combination of (1) the number ofstandard deviations for a 30-day readmission rate and (2) thephysician's contribution margin. In embodiments, the result metric mayalso be a combination of (1) the value metric of wRVUs for a physicianand (2) the quality metric of readmission rate for the physician. Inembodiments, the result metric may be a combination of (1) the patientaccess value metrics for the physician and (2) the quality metric ofemergency department visits.

At operation 210, an insight for the physician is determined. Inembodiments, the insight for the physician is an insight for use by thehealth system for how to handle the physician. For instance, an insightmay be related to helping increase the profile of a particular physicianwith other physicians within the health system. Additionally, insightsmay include types of training that the particular physician shouldreceive. The insight may be determined based on the result metric. Forexample, on the one hand, if the result metric is lower than the averageresult metric for physicians in a health system, the physician may needadditional training. On the other hand, a physician that has an aboveaverage result metric may be considered a top contributor or valuablemember to the health system. The particular insights, however, maychange when the type of value metric and the type of quality metric arechanged. The insights may also be dependent on additional factors, suchas physician attributes (also referred to as physician facts), such asif the physician is currently employed. For example, if the physician isunemployed, the insight may indicate to hire the physician if the othermetrics utilized in determining the insight are positive. If thephysician is employed and has poor associated metrics, the insight mayindicate that the physician is a low priority.

In embodiments, where the value metric is the revenue share for thephysician and the quality metric is the Z-score for the physician, a setof insights may be made based on those two metrics combined as a resultmetric. For example, the revenue share may be a percentage between 0%and 100%. The Z-score may be represented as a number of standarddeviations from the mean Z-score for physicians in the health system. Aresult metric may be determined as a graph coordinate or one-by-twomatrix entry, as discussed above, which may be represented as [revenueshare, Z-score]. The result metric may be considered, for example, infour segments for use in determining insights. The four segments may berepresented by ranges as follows: (1) [>50%, >0], (2) [<50%, >0], (3)[>50%, <0], and (4) [<50%, <0]. An insight may be made based on thesegment in which the physician's result metric falls. For example, ifthe result metric falls within range (1), the physician is a topcontributor to the health system. If the result metric falls withinrange (2), the physician may be seen as growth opportunity. If theresult metric falls within range (3), the physician may be viewed as acandidate for quality improvement who may need additional support. Ifthe result metric falls within range (4), the physician may been seen asa low priority physician. Additional segments based on narrower rangesmay be determined and additional insights provided based on theadditional segments.

In embodiments, where result metric is based on the value metric ofwRVUs for a physician and the quality metric of HEDIS metrics for thephysician, the insights may be similar to those discussed above. Forinstance, a result metric indicating high wRVUs and high HEDIS metricsmay correspond to an insight that physician is a top contributor. Aresult metric indicating high wRVUs and a low HEDIS metrics maycorrespond to an insight that the physician is a quality improvementcandidate. A result metric indicating low wRVUs and a low HEDIS metricsmay correspond to an insight that the physician is a low priority. Aresult metric indicating low wRVUs and a high HEDIS metrics maycorrespond to an insight that the physician has potential opportunityfor improvement.

In embodiments, where the result metric may be a combination of thepatient access value metrics for the physician and the quality metric ofemergency department visits, the insights may also be similar to thoseabove. For example, a result metric indicating high patient accessmetrics and low emergency department visits may correspond to an insightthat the physician is a top contributor. A result metric indicating highpatient access metrics and high emergency department visits maycorrespond to an insight that the physician is a low priority who mayhave potential quality issues. A result metric indicating low patientaccess metrics and high emergency department visits may correspond to aninsight that patients are not being seen but are instead going to theemergency department, and the physician may need additional assistanceand is a quality improvement candidate. A result metric indicating highpatient access metrics and low emergency department visits maycorrespond to an insight that the physician is a potential growthopportunity because the physician is not seeing many patients.

In another example, the result metric may be a combination of the riskadjusted average costs per episode value metric and the quality metricof avoidable admissions. In that example, the insights may be similar tothose discussed above. For instance, a result metric indicating low riskadjusted average costs per episode and low avoidable admissions maycorrespond to an insight that physician is a top contributor. A resultmetric indicating low risk adjusted average costs per episode and highavoidable admissions may correspond to an insight that the physician isa quality improvement candidate. A result metric indicating high riskadjusted average costs per episode and low avoidable admissions maycorrespond to an insight that the physician has a potential opportunityfor improvement. A result metric indicating high risk adjusted averagecosts per episode and high avoidable admissions may correspond to aninsight that the physician is a low priority.

In another example, the result metric may be a combination of per memberper month costs and patient risk. Such a result metric would allow forinsights that identify outliers. For instance, high risks are generallyassociated with high costs and low risks are associated with low costs.As such, where the result metric indicates that a physician has high permember per month costs and low patient risk metrics, the physician havea potential opportunity for improvement. Conversely, a result metricindicating that the physician has low per member per month costs andhigh patient risk metrics would correspond to an insight that thephysician is a top contributor and a potential source for bestpractices.

The insight may also be based on a result metric incorporating thequantity metric. Such a result metric may be represented as athree-dimensional coordinate or a one-by-three matrix entry, such as[value metric, quality metric, quantity metric]. In some embodiments,each metric may be represented by the number of standard deviations fromthe mean. In such embodiments, the insights may be based on whether eachmetric is above or below average. Similarly, the insights may also bebased on whether each metric is above or below a threshold. For example,the insight could be based on whether a physician contributes more orless than one-million dollars. With that type of basis for insights,eight possible insights may be created as shown in FIG. 2B. Additionalinsights may be created through additional segmentation of ranges foreach of the values.

Returning to FIG. 2A, at operation 212, the metrics and insight for thephysician are displayed. In embodiments, the value metric, the qualitymetric, and the quantity metric may each be displayed along with theinsight for the physician. In embodiments, only a subset of the metricsor the insight may be displayed. In an example embodiment, the metricsand insights may be displayed on a graph, chart, or plot. In certainembodiments, the y-axis of the chart may be representative of the valuemetric and the x-axis may be representative of the quality metric, orvice versa. A physician indicator (also referred to herein as“indicator”) may be displayed at the appropriate position or coordinaterepresenting the physician's result metric. Additionally, inembodiments, the size of the physician indicator may also represent thequantity metric or correlate with the value of quantity metric. Thecolor, texture, or another feature (e.g., a visual feature) of thephysician indicator may also represent the insight for the physician. Alegend may also be displayed, where the legend provides the relationshipand/or definition of the colors, textures, or other features ofphysician indicators correspond to particular insights. Additionally,the physician indicator may be displayed among other physicianindicators. The other physician indicators may represent the metrics andinsights for other physicians associated with the health system.Embodiments of interfaces utilized to display the metrics and insightsare discussed below. Additional display methods may also be utilized,such as three-dimensional charts wherein each dimension represents aseparate metric. For example, the x-axis may represent the qualitymetric, the y-axis may represent the value metric, and the z-axis mayrepresent the quantity metric.

FIG. 3A depicts a user interface 300 for selecting and customizing themetrics to be displayed in a physician performance user interface. Theuser interface 300 may include the display of elements within a windowin a computing display. The user interface 300 includes several tabs forselection by the user, including a segmentation tab 302. Upon receivinga selection of the segmentation tab 302, the user interface 300 displaysa button 304 for selection of preset metrics to be displayed. Uponreceiving a selection of the button 304, a drop-down list 306 withmultiple presets is displayed. The multiple presents in the drop-downlist 306 represent different preset options for physician performanceanalytics that a user may select. For instance, two categories aredisplayed in the drop-down list 306: Value-Based Care andFee-For-Service. Within each of those categories are multiple presetoptions that may be selected. Each preset option defines which valuemetric, quality metric, and quantity metric will be utilized in theinterface.

In embodiments of the invention, upon determining that a selectiondevice is hovering on, or has selected, a particular preset, a pop-upbox 308 or other graphical user interface window is displayed in theuser interface 300. The pop-up box 308 displays the metrics that will bedisplayed in the user interface, including the value metric, the qualitymetric, and the quantity metric. For example, in the example depicted inFIG. 3A, upon detecting a selection device hovering above the preset“Readmission Impact on Margin Growth,” the pop-box 308 displays that thequality metric will be displayed on the x-axis and will be the standarddeviation for the 30-day readmission rate for physicians. The pop-up box308 also indicates that the value metric will be displayed on the y-axisand will be the contribution margin for physicians. The pop-up box 308further indicates that the quantity metric will be represented by thebubble size of the physician indicator and will be the attending revenueshare for the physicians. Upon selection of a preset, the drop-down list306 collapses displaying the selected preset. Upon selection of theapply button 310 after a selection of a present, a graphicalrepresentation of the metrics is displayed in the user interface 300, asdepicted in FIG. 3B and discussed below.

In embodiments, a selection interface, such as a drop down list, may beprovided for each of the metrics. For instance, a first selectioninterface may be provided for selection of the value metric, a secondselection interface may be provided for selection of the quality metric,and a third selection interface may be provided for selection of thequantity metric. Upon selection of the apply button 310, a graphicalrepresentation of the selected metrics may be displayed. Those of skillin the art will appreciate that other options are possible for receivingselection of the metrics.

FIG. 3B depicts an example of a user interface for displaying themetrics and insights for physicians. As depicted in FIG. 3B, the userinterface includes a physician analysis chart 312 that displays themetrics and insights for physicians based on the selection of a presetfrom the drop-down list 306. The value metric is represented on they-axis 316 and the quality metric is represented on the x-axis 318 ofthe chart 312. A title 314 above the chart 312 states the metricsinvolved along with other potential information or caveats concerningthe basis of the metrics. The value metric represented on the y-axis 316may have an appropriate scale depending on the metric represented. Forexample, as depicted in FIG. 3B, the value metric represented on they-axis 316 is the contribution margin of a physician. As such, the scalefor the y-axis 316 is in thousands of dollars. The quality metricrepresented on the x-axis 318 may also have an appropriate scale. Asdepicted in FIG. 3B, the quality metric represented on the x-axis 318the standard deviation for the 30-day readmission rate. As such, thescale for the x-axis 318 is the number of standard deviations from themean, where the center of the x-axis 318 indicates zero standarddeviations, or the average 30-day readmission rate. In the particularexample depicted in FIG. 3B, the number of negative standard deviations(indicating a less-than-average 30-day readmission rate) is shown to theright of center of the x-axis 318. The negative standard deviations areshown to the right because, traditionally, more positive results areshown to the right of center, and having a lower 30-day readmission rateis a positive quality for a physician.

Within the chart, multiple physician indicators 322A-I are displayedalong with a segmentation indicator 320 and an insight legend 324. Eachof the physician indicators 322A-I are positioned on the chart 312 at acoordinate corresponding to the physician's result metric. As depicted,each of the physicians represented by physician indicators 322A-I havedifferent result metrics, as represented by the different locations ofthe physician indicators 322A-I. For example, the physician representedby physician indicator 322H has a value metric that is higher than thevalue metric for any other physician. The physician represented byphysician indicator 322H also has a lower 30-day readmission rate thanany of the other physicians represented in the chart 312.

The size of the physician indicators 322A-I represented the quantitymetric for the physician. In the example depicted in the FIG. 3B, thequantity metric is the revenue share for a particular physician. Wherethe physician has a higher associated revenue share, the correspondingphysician indicator will be larger than that of a physician with asmaller revenue share. For example, as depicted in FIG. 3B, thephysician represented by physician indicator 322H has a smaller revenueshare than the physician represented by physician indicator 322I. Thesize of the bubble may be proportional to the difference of thephysician with the lowest value for a quantity metric and the physicianwith the highest value for the quantity metric. For instance, thephysician represented by physician indicator 322E may have a revenueshare value of 85%, and the physician represented by physician indicator322I may have a revenue share value of 100%. Even though there is only a15% difference between the two physician indicators, the bubble size ofthe physician indicator 322I is substantially bigger than the physicianindicator 322E because the size is relative to the 15% difference.

The insights determined for the physicians are also displayed. Asdepicted in FIG. 3B, the insights for the physicians are displayed asdifferent textures or colors of the physician indicators 322A-I. Aninsight legend 324 is displayed in chart 312. The insight legend 324shows the correlation between textures or colors and insights. In theexample depicted in FIG. 3B, there are four separate insights providedfor the physicians represented in the chart 312. The four insights inthe illustrated example provide insight as to whether the physician is atop contributor, a growth target, an optimization target, or a qualityimprovement target. The insights in the illustrated example are based ona result metric that is based on the value metric, the quality metric,and the quantity metric. For example, the physician represented byphysician indicator 322G has a provided insight that the physician is agrowth target, in part, because the physician an above average qualitymetric and an above average contribution margin, but has a smallassociated revenue share. The physician represented by physicianindicator 322F has an insight that the physician is a qualityimprovement target, in part because the physician has a below averagequality metric.

FIG. 3C depicts another element of the user interface for displayingphysician performance analysis. As depicted in FIG. 3C, a tableincluding information about physicians' metrics is displayed. Themetrics displayed in the table are the same metrics that wererepresented in the chart 312 in FIG. 3B. As such, in some embodiments,the chart in FIG. 3C may be displayed below the chart 312. A user may beable to scroll down in the window to see the table below the chart. Inembodiments, the table may be displayed on a separate page or in aseparate window. The table displays a list of the physicians' names orother identifiers of physicians are shown in the first column 326. Inthe second column 328, the value metric is displayed. In the thirdcolumn 330, the quality metric is displayed. In the fourth column 332,the quantity metric is displayed. For example, in the example depictedin FIG. 3C, the value metric is the standard deviation for the 30-dayreadmission rate for a particular physician, the quality metric is thecontribution margin for the particular physician, and the quantitymetric is the revenue share for the physician. Those metrics correspondto the same metrics represented in the chart 312 of the example depictedin FIG. 3B. Other arrangements of the data shown in FIG. 3C arepossible.

The physicians listed in column one 326 of the table correspond tophysicians displayed in the chart 312 depicted in FIG. 3B. The tablealso displays the corresponding values for the metrics of thephysicians. For example, as shown in the table, Physician H has a valuemetric of −0.45σ, a quality metric of $2.82M, and a revenue share of89%. As such, Physician H corresponds to the physician represented byphysician indicator 322H in chart 312 in FIG. 3B. In addition to thevalues of the metrics shown in the table, the insights for thephysicians are also represented in the table. Next to each of thephysicians' names in the first column 326 is a circle with the samecoloring or texture as the corresponding physician indicator 322A-I inchart 12.

The user interface further includes a results number control 336. Theresults number control 336 allows a user to view a particular number ofresults. Upon selection of the results number control 336, a drop-downlist may be displayed listing the possible number of results to display.

Also included in the user interface may be an export button 334. Theexport button 334 allows a user to export data or results from the userinterface. For example, a user may check the boxes next to the names ofthe physicians for which the user desires to export results. Uponselection of the export button 334, the values for the metrics for theselected physicians are exported, for example to a separate spreadsheetor to another application or storage location. In embodiments, a chartsimilar to the chart 312 will also be exported with the physicianindicators corresponding to the selected physicians being displayed inthe exported chart.

FIG. 3D depicts another example of a user interface for displayingphysician performance analytics. A physician analysis chart 346 isdepicted in FIG. 3D. The chart 346 is similar to the chart 312 from FIG.3B, and the chart 346 displays the physician indicators 350A-H. They-axis 342 of chart 346 represents a value metric for physicians and thex-axis 344 of the chart 346 represents a quality metric for physicians.In embodiments where the value metric is revenue share and the qualitymetric is a Z-score for the physician, as depicted in FIG. 3D, thequality metric scale may be based on the number of standard deviationsfrom the mean Z-score for all physicians in the health system. In theillustrated example, the middle of the scale on axis 344 would indicatethe mean, i.e., zero standard deviations from the mean. Left of thecenter of the axis 344 is representative of Z-scores that are less thanthe mean Z-score, and right of the center of the axis 344 isrepresentative of Z-scores that are higher than the mean Z-score. Forthe value metric axis 342, the center of the axis represents a 50%revenue share, with values higher than 50% being above the center of thevalue metric axis 342. Therefore, the physician represented by thephysician indicator 350A has a revenue share metric that is higher than50%, but the physician's Z-score is below average.

The size of the physician indicators 350A-H represent a quantity metricfor a physician. In embodiments, the quantity metric is the case volumefor a physician. In embodiments, the chart indicates that the physicianrepresented by physician indicator 350C has a larger case volume thanthe physician represented by physician indicator 350D, but a smallercase volume than the physician represented by physician indicator 350F.For example, the physician represented by physician 350F has a high casevolume, but a low quality metric and a low revenue share.

A key 354 may also be displayed in or near the chart 346. The key 354may display additional information about the metrics that arerepresented in the chart 346. For instance, the key 354 may indicate howthe quantity metric is displayed. As depicted in FIG. 3D, the key 354notes that the bubble size is representative of the quantity metric,which is the case volume for the example depicted. In the depictedexample, the key 354 also displays the methodology for calculating theZ-score that is used as the quality metric. Specifically, the key 354shows that the Z-score is a weighted score based on the 30-dayreadmission rate, the mortality rate, the complications of care rate fora physician.

Insights for the physicians are also displayed. As depicted in FIG. 3D,the insights for the physicians are displayed as different textures orcolors of the physician indicators 350A-H. An insight legend 352 isdisplayed in or near the chart 346. The insight legend 352 shows thecorrelation between textures or colors and insights. In the exampledepicted in FIG. 3D, there are four separate insights provided for thephysicians represented in the chart 346. As depicted, one insightdetermined may be that a physician is a growth opportunity and thereshould be a recruiting focus. Another insight is that a physician is atop contributor. Yet another insight is that a physician is a candidatefor quality improvement and may require support. Still another insightis that a physician is a low priority. These insights may be based onthe segment of the chart 346 in which the corresponding physicianindicator is located. For instance, all physician indicators in theupper left-hand segment, as defined by the segment indicators 348, areconsidered to be quality improvement candidates, whereas all physicianindicators in the upper right-hand segment may be considered all to betop contributors. Additional segments may be displayed in embodimentsand additional insights that are based on additional segments may alsobe provided.

In user interface depicted in FIG. 3D, the physician's name associatedwith a physician indicator may also be displayed as well as the actualvalues for the quality metric, value metric, and quantity metric. Inembodiments, upon a detection that a selection device, such asappointing device is hovering over a physician indicator, a pop-up box358 or interface window containing the physician's name associated witha physician indicator, the value for the quality metric, the value forthe value metric, and the value for the quantity metric. In embodiments,a selection device may comprise a pointing device such as a mousepointer, a stylus, a user's finger when using a touch-input device, etc.In embodiments, the pop-up box 358 is also displayed upon a selection ofa physician indicator. In some embodiments, all or some of theinformation displayed in pop-up box 358 may be displayed directly in thephysician indicator. As depicted in FIG. 3D, upon detection of selectiondevice hovering above physician indicator 350F, the pop-up box 358 isdisplayed. The pop-up box 358 displays the name of the name of thephysician, here—Thomas Haverford MD, associated with physician indicator350F. Also displayed in the pop-up box 358 are the values for the valuemetric, quality metric, and quantity metric associated with ThomasHaverford. In the example depicted, Dr. Thomas Haverford has anassociated revenue share value of 16%, a Z-score that is 0.325 standarddeviations less than the mean, and a case volume of 390.

In some embodiments, upon a selection of the physicians name in thepop-up box 358, a new page with additional information on the physicianmay be displayed. The additional information may also be displayed uponselection of the physician indicator itself. The additional informationmay be compiled and displayed as a physician performance analysis, asdepicted in FIGS. 4A-4B and described below. In embodiments, theadditional information includes additional value metrics, qualitymetrics, and quantity metrics.

FIGS. 4A-B depict an example of a physician performance analysis 400. Inembodiments, the physician performance analysis 400 is primarily for asingle physician. The physician performance analysis may be accessed,for example, from the user interface 346 as discussed above by selectinga physician indicator or a physician name in a pop-up box or interfacewindow. The physician performance analysis may also be accessed bysearching for a physician or by selecting a physician from another userinterface. The name of the physician is displayed in the title block402. In the depicted example, the particular physician for whom theperformance analysis relates is Dr. Michaela Quinn.

A performance summary 404 is provided for the physician in the physicianperformance analysis 400. The performance summary 404 provides anoverview of the physician's performance. In some embodiments, theperformance summary 404 includes scores or rankings, such as rankingsbased on aggregate quality or quantity scores, for the physician acrossdifferent categories. In the example depicted in FIG. 4A, five separateranks for Dr. Michaela Quinn are included in the performance summary404. One exemplary ranking is the physician's clinically integrated (CI)network scorecard in a section 406 that indicates the physician'sranking against other physicians in the CI network. Another ranking isthe Medicare shared savings ranking in a section 408. Another ranking isthe length of stay reduction initiative in a section 410. Yet anotherranking is the PQRS quality physicians ranking in a section 412. Stillanother ranking is the healthy heart program rating in a section 414.The rankings may be initiatives that the health system is trackingagainst. Any number of rankings may be incorporated in the physicianperformance analysis 400, subject to applicable law. In embodiments,these rankings may also be omitted from the physician performanceanalysis 400.

Following the performance summary may be a more detailed view of metricsassociated with the physician. The displayed metrics may be arrangedinto different categories or sections. For example, as depicted in FIG.4A-B, there are five separate sections: a quality of care section 416, acost and utilization section 418, a market and loyalty section 420, apanel management section 422, and an access and efficiency category 424.Within each section, metrics that are associated with each category aredisplayed for the physician. For example, quality of care metrics mayinclude metrics such mortality rate and the percentage of 30-dayreadmissions; costs and utilization metrics may include average costsand average contribution margin per inpatient case and the average;market and loyalty metrics may include total revenue and differentrevenue shares; panel management metrics may include utilization ratesand average costs per episode; and access and efficiency metrics mayinclude average time for a new patient appointment and availablecapacity for a physician. In embodiments, such quality of care metrics,among others, may be used in determining the quality metric calculatedand displayed in the charts discussed above with respect to FIGS. 3A-D.Similarly, the cost and utilization metrics and market and loyaltymetrics, among others, may be used in determining the value metriccalculated and displayed in the charts discussed above with respect toFIGS. 3A-D.

Multiple values for each of the metrics may also be displayed. In someembodiments, the physician's actual value for the metric, the targetvalue for the metric, and the physician's standard deviation from themean may all be displayed. In the example depicted in FIGS. 4A-B, theactual value for the metrics is displayed in an actual value column 430,the target value for the metric is displayed in a target value column428, and the number of standard deviations value is displayed in thestandard deviation column 426.

FIG. 5 depicts a process flow for making a referral recommendation for aphysician. At operation 502, a value metric is received for a physician.The value metric may be any of the value metrics described above. Atoperation 504, a quality metric is received for the physician. Thequality metric may be any of the quality metrics described above. Atoperation 506 a quantity metric may be received. The value metric,quality metric, and quantity metric may be selected or customized viauser input, subject to applicable law. Receiving the metrics may includereceiving any combination, in any order of the value metric, the qualitymetric, and/or the quantity metric from the sources 104, 106, 108, 110,112, 114, 116 depicted in FIG. 1. In embodiments, receiving the metricsmay also comprise an interface module 102B receiving the metrics from adatabase 102A within the physician performance computing system 102.

Based on the value metric and the quality a metric (and in someembodiments the quantity metric), a result metric is determined atoperation 508. The result metric may be any of the result metricsdiscussed above and may be determined by any of the methods discussedabove.

At operation 510, a referral recommendation is determined for thephysician, subject to applicable law. When a physician or a healthsystem needs to refer a patient to another physician, it is useful tohave recommendations on whether or not a certain physician isrecommended. The referral recommendation determined in operation 510provides a recommendation concerning the preference in recommending aparticular physician. For instance, where a user enters a physician'sname into a user interface as a possible candidate for a referral, theuser interface may provide the recommendation regarding the physician.In embodiments, the referral recommendation may also be integrated intosearch results for a physician referral. For example, a positiverecommendation may increase the physician's ranking in a search resultslist, while a negative recommendation may decrease a physician's rankingin the search results list.

In embodiments, the referral recommendation is based on the resultmetric. The referral recommendation may also be based on particularsegmentations or ranges of metrics, similar to the insights discussedabove. The referral recommendation may also be determined via additionalalgorithms to determine a value representative of the recommendation.The value representative of the recommendation may then be incorporatedinto search algorithms for physician referrals.

FIG. 6 depicts an example of a referral interface 600 for receivingreferrals based on referral recommendations. The referral interface 600may include information regarding the patient 602, the referringphysician 606, and the type of referral 604 that is being made.

As shown in FIG. 6, the referral interface includes a search component608. The search component 608 receives user input to find a physician.Within the search component 608, there are several data entry fields oroptions for refining a search for a physician. In the depicted example,a specialty search list 610 is displayed. The specialty search list 610allows a user to select a specialty for a referral physician. Asub-specialty option 612 may also be included to allow for searchrefinements by sub-specialty. An insurance plan option 614 and a plantype option 616 may also be included to allow for search refinements byinsurance plan and insurance plan type. A geographic location-basedoption, such as a zip code option 618, may also be included to allow forsearch refinement by geographic area. A physician name search option 620may be included to allow for a search refinement by the name of aphysician. A preferred language option 622 option may be included toallow for search refinement by the languages spoken by a referralphysician. Upon selection of the find button 642, a referral search isexecuted and a results list of physicians is displayed.

The results list contains entries for the referral physicians matchingthe search criteria according to a search algorithm. The referralphysicians within the results list may be listed in sections containingadditional information about the physician. For instance, as depicted inFIG. 6, three referral physicians were included in the results list:Michaela Quinn, Joseph Gibbs, and Ron Swanson. Each of the physicianshas a different section with additional information about the physician.

In the Dr. Quinn section 624, the physician's name is displayed alongwith further information about Dr. Quinn. In embodiments, multiplecheckboxes are displayed in the referral physician section 624 for someor all of the search options utilized in search component 608. Forinstance, the Dr. Quinn section 624 includes a checkbox for specialty,subspecialty, insurance match, location, and language. In the exampledepicted, all the check boxes are displayed as checked, indicating thatthe Dr. Quinn's attributes match the searched options. The physician'sspecialty may also be displayed, along with the physician's address andthe health system to which the physician belongs. Other informationrelevant to the referral may also be provided, as necessary.

Within each physician section may be two actionable buttons: a referralbutton 626 and a view profile button 628. Upon selection of the referralbutton 626, a referral will be made to the physician within therespective physician section. For example, upon selection of thereferral button 626, Dr. Quinn is referred (or an additional userinterface is provided to facilitate such referral). Upon selection ofthe view profile button 628, additional information about the physicianmay be displayed. The additional information may be arranged anddisplayed, in embodiments, as a physician performance analysis 400 asdepicted in FIGS. 4A-B. For example, upon selection of the view profilebutton 628, additional information about Dr. Quinn is displayed.

The physician sections for Dr. Gibbs 630 and Dr. Swanson 636 aresubstantially similar to the Dr. Quinn section 624. Each of the sectionsdisplays checkboxes for search options. For all three physicians in theresults list, all the displayed check boxes are displayed as beingchecked. As such, each of the search criteria is matched. The order orrank of the physicians in the results list thus depends on additionalfactors, such as the recommendation determined in operation 510 in FIG.5. For example, Dr. Quinn may have a more positive result metric thaneither Dr. Gibbs or Dr. Swanson. As such, Dr. Quinn is displayed higherin the results list than Dr. Gibbs or Dr. Swanson.

FIG. 7 illustrates one example of a suitable operating environment 700in which one or more of the present embodiments may be implemented. Thisis only one example of a suitable operating environment and is notintended to suggest any limitation as to the scope of use orfunctionality. Other well-known computing systems, environments, and/orconfigurations that may be suitable for use include, but are not limitedto, personal computers, server computers, hand-held or laptop devices,multiprocessor systems, microprocessor-based systems, programmableconsumer electronics such as smartphones, network PCs, minicomputers,mainframe computers, distributed computing environments that include anyof the above systems or devices, and the like.

In its most basic configuration, the operating environment 700 typicallyincludes at least one processing unit 702 and memory 704. Depending onthe exact configuration and type of computing device, the memory 704(storing, among other things, sequential chains constructed as describedherein) may be volatile (such as RAM), non-volatile (such as ROM, flashmemory, etc.), or some combination of the two. Memory 704 may storecomputer instructions related to generating a physician indicator,and/or displaying the various user interface embodiments disclosedherein. The memory 704 may also store computer-executable instructionsthat may be executed by the processing unit 702 to perform the methodsdisclosed herein.

This most basic configuration is illustrated in FIG. 7 by a dashed line706. Further, the environment 700 may also include storage devices(removable, 708, and/or non-removable, 710) including, but not limitedto, magnetic or optical disks or tape. Similarly, the environment 700may also have input device(s) 714 such as a keyboard, mouse, pen, voiceinput, etc. and/or output device(s) 716 such as a display, speakers,printer, etc. Also included in the environment may be one or morecommunication connections, 712, such as LAN, WAN, point to point, etc.

The operating environment 700 typically includes at least some form ofcomputer readable media. Computer readable media can be any availablemedia that can be accessed by the processing unit 702 or other devicescomprising the operating environment. By way of example, and notlimitation, computer readable media may comprise computer storage mediaand communication media. Computer storage media includes volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information such as computer readableinstructions, data structures, program modules or other data. Computerstorage media includes, RAM, ROM, EEPROM, flash memory or other memorytechnology, CD-ROM, digital versatile disks (DVD) or other opticalstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, or any other tangible or non-transitorymedium which can be used to store the desired information. Computerstorage media does not include communication media.

Communication media embodies computer readable instructions, datastructures, program modules, or other data in a modulated data signalsuch as a carrier wave or other transport mechanism and includes anyinformation delivery media. The term “modulated data signal” means asignal that has one or more of its characteristics set or changed insuch a manner as to encode information in the signal. By way of example,and not limitation, communication media includes wired media such as awired network or direct-wired connection, and wireless media such asacoustic, RF, infrared and other wireless media. Combinations of any ofthe above should also be included within the scope of computer readablemedia. In embodiments, the computer storage media may store physicianindicators and information and instructions to create, modify, orotherwise interact with physician indicators and information.

The operating environment 700 may be a single computer operating in anetworked environment using logical connections to one or more remotecomputers. The remote computer may be a personal computer, a server, arouter, a network PC, a peer device or other common network node, andtypically includes many or all of the elements described above as wellas others not so mentioned. The logical connections may include anymethod supported by available communications media. Such networkingenvironments are commonplace in offices, enterprise-wide computernetworks, intranets and the Internet.

FIG. 8 is an embodiment of a network 800 in which the various systemsand methods disclosed herein may operate. In embodiments, clientdevices, such as client devices 802A and 802B, may communicate with eachother and one or more servers, such as servers 804 and 806, via anetwork 808. In embodiments, a client device may be a laptop, a personalcomputer, a smart phone, a PDA, a netbook, or any other type ofcomputing device, such as the computing device in FIG. 8. Inembodiments, the servers 804 and 806 may be any type of computingdevice, such as the computing device illustrated in FIG. 7. The network808 may be any type of network capable of facilitating communicationsbetween the client devices 802A and 802B and one or more servers 804 and806. Examples of such networks include, but are not limited to, LANs,WANs, cellular networks, and/or the Internet.

In embodiments, the various systems and methods disclosed herein may beperformed by one or more server devices. For example, in one example, asingle server, such as the server 804 may be employed to perform thesystems and methods disclosed herein. The client device 802 may interactwith the server 804 via network 808 in order to access information suchas, information about physician indicators and information. In furtherembodiments, the client device 806 may also perform functionalitydisclosed herein, such as by displaying one of the disclosed forms andcollecting information from a user.

In embodiments, the methods and systems disclosed herein may also beperformed using a distributed computing network, or a cloud network.Data may be stored locally or remotely. One skilled in the term“receiving” is not intended to be limiting, and may include passivereceipt and or active retrieval, such as pull or push type datatransfer, or a combination thereof. In embodiments, the methods andsystems disclosed herein may be performed by two or more servers, suchas the servers 804 and 806. Although a particular network embodiment isdisclosed herein, one of skill in the art will appreciate that thesystems and methods disclosed herein may be performed using other typesof networks and/or network configurations.

Although specific embodiments were described herein and specificexamples were provided, the scope of the invention is not limited tothose specific embodiments and examples. One skilled in the art willrecognize other embodiments or improvements that are within the scopeand spirit of the present invention. Additionally, the specificembodiments and examples described herein may be combined with oneanother. Therefore, the specific structure, acts, or media are disclosedonly as illustrative embodiments. The scope of the invention is definedby the following claims and any equivalents therein.

What is claimed is:
 1. A method for displaying physician analytics, themethod comprising: receiving, at a processor, a value metric associatedwith a first physician; receiving, at the processor, a value metricassociated with a second physician; receiving, at the processor, aquality metric associated with the first physician and a quality metricassociated with the second physician, wherein the value metric and thequality metric are based on data from at least one of internal andexternal data sources, wherein an Application Program Interface (API) isused to share the data between the processor and the at least one of theinternal and external data sources while the internal and external datasources house the data separately from a system comprising theprocessor; based on the value metric and the quality metric for thefirst physician, and based on the value metric and the quality metricfor the second physician, automatically generating, using the processor,a result metric for the first physician; based on the value metric andthe quality metric for the second physician, and based on the valuemetric and the quality metric for the first physician, automaticallygenerating, using the processor, a result metric for the secondphysician, wherein the result metric for the first physician and theresult metric for second physician are represented by at least one of acoordinate and a one-by-two matrix entry in a database, wherein twovalues in the one-by-two matrix entry are the value metric and thequality metric; based on the result metric for the first physician, andrelative to the result metric for the second physician, automaticallygenerating an insight for the first physician; based on the resultmetric for the second physician, and relative to the result metric forthe first physician, automatically generating an insight for the secondphysician; automatically generating, using the processor, a display fora user interface, comprising: a first axis representing the valuemetric; a second axis representing the quality metric; a first physicianinsight indicator, a visual characteristic of the first physicianinsight indicator representing the insight for the first physician,plotted with respect to the first and second axes, wherein a position ofthe first physician insight indicator represents the value metric forthe first physician, the quality metric for the first physician, and theresult metric for the first physician; a second physician insightindicator, a visual characteristic of the second physician insightindicator representing the insight for the second physician, plottedwith respect to the first and second axes, wherein a position of thesecond physician insight indicator represents the value metric for thesecond physician, the quality metric for the second physician, and theresult metric for the second physician; and a legend comprising alisting of at least one first physician insight and the at least onesecond physician insight; and outputting the user interface.
 2. Themethod of claim 1, wherein displaying the first axis is one axis of achart and the second axis is another axis of the chart.
 3. The method ofclaim 1, further comprising receiving, at the processor, a quantitymetric for the first physician, wherein the display further comprises adisplay of the quantity metric for the first physician.
 4. The method ofclaim 3, wherein: the display of the quantity metric for the firstphysician comprises a size of the first physician insight indicatorplotted with respect to the first and second axes, wherein the size ofthe first physician insight indicator corresponds to a value of thequantity metric for the first physician.
 5. The method of claim 3,wherein the quantity metric is based on at least one piece of dataselected from the group consisting of: a number of patients of the firstphysician, a case volume for the first physician, a number of operationsfor the first physician, revenue share for the first physician, and thevolume for the first physician, and the revenue for the first physician.6. The method of claim 3, wherein the display further comprisingdisplaying specific values for the value metric, the quality metric, andthe quantity metric.
 7. The method of claim 3, wherein the generateduser interface is operable to receive user selections of at least one ofthe value metric, the quality metric, and the quantity metric.
 8. Themethod of claim 1, wherein the insight for the first physician is basedon one or more of: a type of training for the first physician, a hiringdecision for the first physician, or a profile for the first physician.9. The method of claim 8, wherein: the visual characteristic of thefirst physician insight indicator is a color of the first physicianinsight indicator; and the legend correlates the color of the firstphysician insight indicator with a text description of the insight forthe first physician.
 10. The method of claim 9, wherein the visualcharacteristic of the first physician insight indicator insight is basedon a location of the first physician insight indicator with respect tothe first axis and the second axis.
 11. The method of claim 9, wherein:the first axis and the second axis are two axes of a chart; the chartcomprises multiple segments; and each segment corresponds to a differentinsight.
 12. The method of claim 1, wherein the value metric indicatesthe first physician's value to a health system.
 13. The method of claim1, wherein the value metric is based on at least one or more of thegroup consisting of: contribution margin and revenue share.
 14. Themethod of claim 1, wherein the quality metric indicates a quality ofcare provided by the first physician.
 15. The method of claim 1, whereinthe quality metric is based on at least one or more pieces of data fromthe group consisting of: 30-day readmission rate, mortality rate, andcomplications of care rate.
 16. The method of claim 1, furthercomprising receiving, at the processor, a selection of the firstphysician insight indicator and, in response, generating a displaycomprising additional metrics for the first physician.
 17. The method ofclaim 1, wherein the value metric is received from a first source andthe quality metric is received from a second source.
 18. A computerstorage media comprising instructions that, when executed by one or moreprocessors, cause at least one of the one or more processors to executea method comprising: receiving, at the processor, a value metricassociated with a first physician; receiving, at the processor, a valuemetric associated with a second physician; receiving, at the processor,a quality metric associated with the first physician and a qualitymetric associated with the second physician, wherein the value metricand the quality metric are based on data from at least one of internaland external data sources, wherein an Application Program Interface(API) is used to share the data between the processor and the at leastone of the internal and external data sources while the internal andexternal data sources house the data separately from a system comprisingthe processor; based on the value metric and the quality metric for thefirst physician, and based on the value metric and the quality metricfor the second physician, automatically generating, using the processor,a result metric for the first physician; based on the value metric andthe quality metric for the second physician, and based on the valuemetric and the quality metric for the first physician, automaticallygenerating, using the processor, a result metric for the secondphysician, wherein the result metric for the first physician and theresult metric for second physician are represented by at least one of acoordinate and a one-by-two matrix entry in a database, wherein twovalues in the one-by-two matrix entry are the value metric and thequality metric; based on the result metric for the first physician, andrelative to the result metric for the second physician, automaticallygenerating an insight for the first physician; based on the resultmetric for the second physician, and relative to the result metric forthe first physician, automatically generating an insight for the secondphysician; automatically generating, using the processor, a display fora user interface, comprising: a first axis representing the valuemetric; a second axis representing the quality metric; a first physicianinsight indicator, a visual characteristic of the first physicianinsight indicator representing the insight for the first physician,plotted with respect to the first and second axes, wherein a position ofthe first physician insight indicator represents the value metric forthe first physician, the quality metric for the first physician, and theresult metric for the first physician; a second physician insightindicator, a visual characteristic of the second physician insightindicator representing the insight for the second physician, plottedwith respect to the first and second axes, wherein a position of thesecond physician insight indicator represents the value metric for thesecond physician, the quality metric for the second physician, and theresult metric for the second physician; and a legend comprising alisting of at least one first physician insight and the at least onesecond physician insight; and outputting the user interface.
 19. Amethod for utilizing physician analytics, the method comprising:receiving, at a processor, a value metric associated with a firstphysician; receiving, at the processor, a value metric associated with asecond physician; receiving, at the processor, a quality metricassociated with the first physician and a quality metric associated withthe second physician, wherein the value metric and the quality metricare based on data from at least one of internal and external datasources, wherein an Application Program Interface (API) is used to sharethe data between the processor and the at least one of the internal andexternal data sources while the internal and external data sources housethe data separately from a system comprising the processor; based on thevalue metric and the quality metric for the first physician, and basedon the value metric and the quality metric for the second physician,automatically generating, using the processor, a result metric for thefirst physician; based on the value metric and the quality metric forthe second physician, and based on the value metric and the qualitymetric for the first physician, automatically generating, using theprocessor, a result metric for the second physician, wherein the resultmetric for the first physician and the result metric for secondphysician are represented by at least one of a coordinate and aone-by-two matrix entry in a database, wherein two values in theone-by-two matrix entry are the value metric and the quality metric;based on the result metric for the first physician, and relative to theresult metric for the second physician, automatically generating aninsight for the first physician; based on the result metric for thesecond physician, and relative to the result metric for the firstphysician, automatically generating an insight for the second physician;automatically generating, using the processor, a display for a userinterface, comprising: a first axis representing the value metric; asecond axis representing the quality metric; a first physician insightindicator, a visual characteristic of the first physician insightindicator representing the insight for the first physician, plotted withrespect to the first and second axes, wherein a position of the firstphysician insight indicator represents the value metric for the firstphysician, the quality metric for the first physician, and the resultmetric for the first physician; a second physician insight indicator, avisual characteristic of the second physician insight indicatorrepresenting the insight for the second physician, plotted with respectto the first and second axes, wherein a position of the second physicianinsight indicator represents the value metric for the second physician,the quality metric for the second physician, and the result metric forthe second physician; and a legend comprising a listing of at least onefirst physician insight and the at least one second physician insight;outputting the user interface; automatically generating, using theprocessor, a referral recommendation for the first physician based onthe result metric for the first physician; and automatically displaying,on the display, the referral recommendation.
 20. The method of claim 19,wherein automatically generating the referral recommendation comprisesadjusting, using the processor, a rank of the first physician in asearch results list for a search for physician referrals.